Overview

Dataset statistics

Number of variables13
Number of observations2351
Missing cells0
Missing cells (%)0.0%
Duplicate rows5
Duplicate rows (%)0.2%
Total size in memory321.7 KiB
Average record size in memory140.1 B

Variable types

Numeric10
Text3

Alerts

Dataset has 5 (0.2%) duplicate rowsDuplicates
item_approx_price is highly overall correlated with item_primary_priceHigh correlation
accurate_description is highly overall correlated with communication and 1 other fieldsHigh correlation
communication is highly overall correlated with accurate_description and 1 other fieldsHigh correlation
shipping_speed is highly overall correlated with accurate_description and 1 other fieldsHigh correlation
item_primary_price is highly overall correlated with item_approx_priceHigh correlation
item_approx_price has 256 (10.9%) zerosZeros
accurate_description has 291 (12.4%) zerosZeros
communication has 291 (12.4%) zerosZeros
shipping_speed has 291 (12.4%) zerosZeros
feedback_pr has 1073 (45.6%) zerosZeros
review_count has 2191 (93.2%) zerosZeros
reasonable_shipping_cost has 295 (12.5%) zerosZeros

Reproduction

Analysis started2024-03-16 20:51:51.359804
Analysis finished2024-03-16 20:52:12.857048
Duration21.5 seconds
Software versionydata-profiling vv4.6.1
Download configurationconfig.json

Variables

item_approx_price
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct954
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3729346
Minimum0
Maximum2.4526318
Zeros256
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:13.059676image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.3035621
median1.516803
Q31.6894366
95-th percentile1.9238636
Maximum2.4526318
Range2.4526318
Interquartile range (IQR)0.38587445

Descriptive statistics

Standard deviation0.54456208
Coefficient of variation (CV)0.39664095
Kurtosis1.6978274
Mean1.3729346
Median Absolute Deviation (MAD)0.19782583
Skewness-1.5849357
Sum3227.7693
Variance0.29654786
MonotonicityNot monotonic
2024-03-16T16:52:13.309090image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 256
 
10.9%
1.612780981 33
 
1.4%
1.468126265 31
 
1.3%
1.402477292 28
 
1.2%
1.516803008 27
 
1.1%
1.168118851 26
 
1.1%
1.468289279 25
 
1.1%
1.554991681 25
 
1.1%
1.303562121 25
 
1.1%
1.516740451 23
 
1.0%
Other values (944) 1852
78.8%
ValueCountFrequency (%)
0 256
10.9%
0.009901152271 1
 
< 0.1%
0.603524297 3
 
0.1%
0.6175694594 9
 
0.4%
0.664699299 4
 
0.2%
0.6726128986 4
 
0.2%
0.6897673619 1
 
< 0.1%
0.7007336701 2
 
0.1%
0.702526715 1
 
< 0.1%
0.7233157493 1
 
< 0.1%
ValueCountFrequency (%)
2.452631842 1
< 0.1%
2.285158947 1
< 0.1%
2.249692494 1
< 0.1%
2.233974887 1
< 0.1%
2.229984135 1
< 0.1%
2.193426521 1
< 0.1%
2.181238365 1
< 0.1%
2.178461244 1
< 0.1%
2.168773092 2
0.1%
2.161885451 1
< 0.1%

accurate_description
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2922161
Minimum0
Maximum5
Zeros291
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:13.548827image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.8
median4.9
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation1.6170722
Coefficient of variation (CV)0.37674528
Kurtosis3.1786538
Mean4.2922161
Median Absolute Deviation (MAD)0.1
Skewness-2.2673635
Sum10091
Variance2.6149224
MonotonicityNot monotonic
2024-03-16T16:52:13.767882image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4.9 946
40.2%
5 696
29.6%
0 291
 
12.4%
4.8 248
 
10.5%
4.7 100
 
4.3%
4.6 43
 
1.8%
4.5 11
 
0.5%
4.4 6
 
0.3%
4.2 4
 
0.2%
4.3 4
 
0.2%
Other values (2) 2
 
0.1%
ValueCountFrequency (%)
0 291
12.4%
3.7 1
 
< 0.1%
3.8 1
 
< 0.1%
4.2 4
 
0.2%
4.3 4
 
0.2%
4.4 6
 
0.3%
4.5 11
 
0.5%
4.6 43
 
1.8%
4.7 100
 
4.3%
4.8 248
10.5%
ValueCountFrequency (%)
5 696
29.6%
4.9 946
40.2%
4.8 248
 
10.5%
4.7 100
 
4.3%
4.6 43
 
1.8%
4.5 11
 
0.5%
4.4 6
 
0.3%
4.3 4
 
0.2%
4.2 4
 
0.2%
3.8 1
 
< 0.1%
Distinct1617
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:14.118170image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length35
Median length29
Mean length13.52063
Min length3

Characters and Unicode

Total characters31787
Distinct characters76
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1377 ?
Unique (%)58.6%

Sample

1st rowpearlwholesale
2nd rowdragonemad
3rd rowSeven Star Solutions
4th rowadalyn1973
5th rowray_6049
ValueCountFrequency (%)
store 63
 
1.8%
and 44
 
1.3%
the 37
 
1.1%
jewellery-exports 31
 
0.9%
pearlwholesale 28
 
0.8%
cecraig 28
 
0.8%
wholesalejewelryer 24
 
0.7%
shop 24
 
0.7%
nature 21
 
0.6%
trading 21
 
0.6%
Other values (1988) 3186
90.8%
2024-03-16T16:52:14.799896image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2910
 
9.2%
a 2286
 
7.2%
o 1794
 
5.6%
r 1768
 
5.6%
s 1732
 
5.4%
i 1713
 
5.4%
l 1620
 
5.1%
t 1479
 
4.7%
n 1361
 
4.3%
1156
 
3.6%
Other values (66) 13968
43.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24424
76.8%
Uppercase Letter 3323
 
10.5%
Decimal Number 2040
 
6.4%
Space Separator 1156
 
3.6%
Dash Punctuation 358
 
1.1%
Connector Punctuation 319
 
1.0%
Other Punctuation 153
 
0.5%
Final Punctuation 8
 
< 0.1%
Math Symbol 3
 
< 0.1%
Other Symbol 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2910
11.9%
a 2286
 
9.4%
o 1794
 
7.3%
r 1768
 
7.2%
s 1732
 
7.1%
i 1713
 
7.0%
l 1620
 
6.6%
t 1479
 
6.1%
n 1361
 
5.6%
c 904
 
3.7%
Other values (16) 6857
28.1%
Uppercase Letter
ValueCountFrequency (%)
S 369
 
11.1%
T 259
 
7.8%
C 255
 
7.7%
A 195
 
5.9%
R 188
 
5.7%
E 174
 
5.2%
L 153
 
4.6%
P 148
 
4.5%
O 140
 
4.2%
N 139
 
4.2%
Other values (16) 1303
39.2%
Decimal Number
ValueCountFrequency (%)
1 333
16.3%
2 326
16.0%
0 287
14.1%
8 206
10.1%
6 176
8.6%
9 163
8.0%
4 162
7.9%
3 155
7.6%
7 141
6.9%
5 91
 
4.5%
Other Punctuation
ValueCountFrequency (%)
' 66
43.1%
. 55
35.9%
& 22
 
14.4%
/ 5
 
3.3%
* 3
 
2.0%
, 2
 
1.3%
Space Separator
ValueCountFrequency (%)
1156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 358
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 319
100.0%
Final Punctuation
ValueCountFrequency (%)
8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27747
87.3%
Common 4040
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2910
 
10.5%
a 2286
 
8.2%
o 1794
 
6.5%
r 1768
 
6.4%
s 1732
 
6.2%
i 1713
 
6.2%
l 1620
 
5.8%
t 1479
 
5.3%
n 1361
 
4.9%
c 904
 
3.3%
Other values (42) 10180
36.7%
Common
ValueCountFrequency (%)
1156
28.6%
- 358
 
8.9%
1 333
 
8.2%
2 326
 
8.1%
_ 319
 
7.9%
0 287
 
7.1%
8 206
 
5.1%
6 176
 
4.4%
9 163
 
4.0%
4 162
 
4.0%
Other values (14) 554
13.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31778
> 99.9%
Punctuation 8
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2910
 
9.2%
a 2286
 
7.2%
o 1794
 
5.6%
r 1768
 
5.6%
s 1732
 
5.5%
i 1713
 
5.4%
l 1620
 
5.1%
t 1479
 
4.7%
n 1361
 
4.3%
1156
 
3.6%
Other values (64) 13959
43.9%
Punctuation
ValueCountFrequency (%)
8
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%

communication
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3349213
Minimum0
Maximum5
Zeros291
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:15.040922image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.9
median5
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation1.632083
Coefficient of variation (CV)0.37649657
Kurtosis3.1940721
Mean4.3349213
Median Absolute Deviation (MAD)0
Skewness-2.2732076
Sum10191.4
Variance2.6636949
MonotonicityNot monotonic
2024-03-16T16:52:15.221807image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
5 1322
56.2%
4.9 557
23.7%
0 291
 
12.4%
4.8 89
 
3.8%
4.7 50
 
2.1%
4.6 27
 
1.1%
4.5 7
 
0.3%
4.4 6
 
0.3%
4.3 1
 
< 0.1%
3.5 1
 
< 0.1%
ValueCountFrequency (%)
0 291
 
12.4%
3.5 1
 
< 0.1%
4.3 1
 
< 0.1%
4.4 6
 
0.3%
4.5 7
 
0.3%
4.6 27
 
1.1%
4.7 50
 
2.1%
4.8 89
 
3.8%
4.9 557
23.7%
5 1322
56.2%
ValueCountFrequency (%)
5 1322
56.2%
4.9 557
23.7%
4.8 89
 
3.8%
4.7 50
 
2.1%
4.6 27
 
1.1%
4.5 7
 
0.3%
4.4 6
 
0.3%
4.3 1
 
< 0.1%
3.5 1
 
< 0.1%
0 291
 
12.4%

shipping_speed
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3403233
Minimum0
Maximum5
Zeros291
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:15.394832image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.9
median5
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation1.6337006
Coefficient of variation (CV)0.37640067
Kurtosis3.2000637
Mean4.3403233
Median Absolute Deviation (MAD)0
Skewness-2.2753425
Sum10204.1
Variance2.6689776
MonotonicityNot monotonic
2024-03-16T16:52:15.619470image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
5 1377
58.6%
4.9 524
 
22.3%
0 291
 
12.4%
4.8 99
 
4.2%
4.7 34
 
1.4%
4.6 15
 
0.6%
4.5 5
 
0.2%
4.1 3
 
0.1%
4.4 1
 
< 0.1%
4.3 1
 
< 0.1%
ValueCountFrequency (%)
0 291
12.4%
4 1
 
< 0.1%
4.1 3
 
0.1%
4.3 1
 
< 0.1%
4.4 1
 
< 0.1%
4.5 5
 
0.2%
4.6 15
 
0.6%
4.7 34
 
1.4%
4.8 99
 
4.2%
4.9 524
22.3%
ValueCountFrequency (%)
5 1377
58.6%
4.9 524
 
22.3%
4.8 99
 
4.2%
4.7 34
 
1.4%
4.6 15
 
0.6%
4.5 5
 
0.2%
4.4 1
 
< 0.1%
4.3 1
 
< 0.1%
4.1 3
 
0.1%
4 1
 
< 0.1%

title
Text

Distinct2295
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:16.032019image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length91
Median length86
Mean length70.713313
Min length6

Characters and Unicode

Total characters166247
Distinct characters146
Distinct categories20 ?
Distinct scripts6 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2251 ?
Unique (%)95.7%

Sample

1st rowFashion Silver Zircon Christmas Xmas Elk Earrings Stud Women Party Jewelry Gift
2nd rowCarly Universal Scanner BMW Diagnostic Best App (iOS/Android) OBD Reader+GIFT !!
3rd rowAqua Red Perfume For Men, Long Lasting & Smooth Jasmine Fragrance 60 ml
4th rowAlfred's Basic Piano Library lot of 3 Lesson, Act/Ear Train, Solo Level A
5th rowPetSpy N10 Ultrasonic Dog Bark Deterrent, 2 Frequency Modes, Barking Control Dog
ValueCountFrequency (%)
764
 
2.8%
new 437
 
1.6%
for 302
 
1.1%
and 203
 
0.8%
blanket 194
 
0.7%
size 179
 
0.7%
throw 178
 
0.7%
vintage 174
 
0.6%
black 173
 
0.6%
car 172
 
0.6%
Other values (6052) 24220
89.7%
2024-03-16T16:52:16.789427image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24814
 
14.9%
e 11998
 
7.2%
a 9113
 
5.5%
r 7916
 
4.8%
i 7672
 
4.6%
o 7638
 
4.6%
n 7506
 
4.5%
t 7102
 
4.3%
l 5463
 
3.3%
s 4682
 
2.8%
Other values (136) 72343
43.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 95644
57.5%
Uppercase Letter 33802
 
20.3%
Space Separator 24822
 
14.9%
Decimal Number 8372
 
5.0%
Other Punctuation 1866
 
1.1%
Dash Punctuation 1057
 
0.6%
Open Punctuation 172
 
0.1%
Close Punctuation 169
 
0.1%
Math Symbol 116
 
0.1%
Final Punctuation 105
 
0.1%
Other values (10) 122
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11998
12.5%
a 9113
 
9.5%
r 7916
 
8.3%
i 7672
 
8.0%
o 7638
 
8.0%
n 7506
 
7.8%
t 7102
 
7.4%
l 5463
 
5.7%
s 4682
 
4.9%
d 3180
 
3.3%
Other values (29) 23374
24.4%
Uppercase Letter
ValueCountFrequency (%)
S 3277
 
9.7%
C 2675
 
7.9%
A 2420
 
7.2%
B 2087
 
6.2%
P 2034
 
6.0%
M 1893
 
5.6%
T 1672
 
4.9%
E 1623
 
4.8%
D 1618
 
4.8%
R 1592
 
4.7%
Other values (19) 12911
38.2%
Other Punctuation
ValueCountFrequency (%)
. 429
23.0%
/ 371
19.9%
, 285
15.3%
" 237
12.7%
' 162
 
8.7%
& 99
 
5.3%
! 82
 
4.4%
* 77
 
4.1%
# 52
 
2.8%
: 29
 
1.6%
Other values (9) 43
 
2.3%
Decimal Number
ValueCountFrequency (%)
0 1570
18.8%
1 1565
18.7%
2 1238
14.8%
5 860
10.3%
3 635
7.6%
6 607
 
7.3%
4 584
 
7.0%
8 445
 
5.3%
9 442
 
5.3%
7 426
 
5.1%
Other Symbol
ValueCountFrequency (%)
39
58.2%
11
 
16.4%
° 9
 
13.4%
® 3
 
4.5%
2
 
3.0%
1
 
1.5%
1
 
1.5%
1
 
1.5%
Other Letter
ValueCountFrequency (%)
5
38.5%
2
 
15.4%
2
 
15.4%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Nonspacing Mark
ValueCountFrequency (%)
3
33.3%
2
22.2%
2
22.2%
1
 
11.1%
1
 
11.1%
Math Symbol
ValueCountFrequency (%)
| 49
42.2%
+ 48
41.4%
~ 18
 
15.5%
× 1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 154
89.5%
[ 16
 
9.3%
{ 2
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 151
89.3%
] 16
 
9.5%
} 2
 
1.2%
Spacing Mark
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Modifier Symbol
ValueCountFrequency (%)
^ 2
40.0%
` 2
40.0%
´ 1
20.0%
Space Separator
ValueCountFrequency (%)
24814
> 99.9%
  8
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1051
99.4%
6
 
0.6%
Final Punctuation
ValueCountFrequency (%)
81
77.1%
24
 
22.9%
Initial Punctuation
ValueCountFrequency (%)
9
81.8%
2
 
18.2%
Format
ValueCountFrequency (%)
 1
50.0%
1
50.0%
Currency Symbol
ValueCountFrequency (%)
$ 8
100.0%
Private Use
ValueCountFrequency (%)
1
100.0%
Other Number
ValueCountFrequency (%)
¼ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 129424
77.9%
Common 36773
 
22.1%
Khmer 24
 
< 0.1%
Cyrillic 22
 
< 0.1%
Inherited 3
 
< 0.1%
Unknown 1
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
24814
67.5%
0 1570
 
4.3%
1 1565
 
4.3%
2 1238
 
3.4%
- 1051
 
2.9%
5 860
 
2.3%
3 635
 
1.7%
6 607
 
1.7%
4 584
 
1.6%
8 445
 
1.2%
Other values (52) 3404
 
9.3%
Latin
ValueCountFrequency (%)
e 11998
 
9.3%
a 9113
 
7.0%
r 7916
 
6.1%
i 7672
 
5.9%
o 7638
 
5.9%
n 7506
 
5.8%
t 7102
 
5.5%
l 5463
 
4.2%
s 4682
 
3.6%
S 3277
 
2.5%
Other values (46) 57057
44.1%
Khmer
ValueCountFrequency (%)
5
20.8%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (4) 4
16.7%
Cyrillic
ValueCountFrequency (%)
а 4
18.2%
к 3
13.6%
у 2
9.1%
р 2
9.1%
г 2
9.1%
ш 2
9.1%
я 2
9.1%
Ч 1
 
4.5%
И 1
 
4.5%
б 1
 
4.5%
Other values (2) 2
9.1%
Inherited
ValueCountFrequency (%)
3
100.0%
Unknown
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165971
99.8%
Punctuation 128
 
0.1%
None 43
 
< 0.1%
Specials 40
 
< 0.1%
Khmer 24
 
< 0.1%
Cyrillic 22
 
< 0.1%
Misc Symbols 11
 
< 0.1%
VS 3
 
< 0.1%
Letterlike Symbols 3
 
< 0.1%
Dingbats 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24814
 
15.0%
e 11998
 
7.2%
a 9113
 
5.5%
r 7916
 
4.8%
i 7672
 
4.6%
o 7638
 
4.6%
n 7506
 
4.5%
t 7102
 
4.3%
l 5463
 
3.3%
s 4682
 
2.8%
Other values (80) 72067
43.4%
Punctuation
ValueCountFrequency (%)
81
63.3%
24
 
18.8%
9
 
7.0%
6
 
4.7%
3
 
2.3%
2
 
1.6%
1
 
0.8%
1
 
0.8%
1
 
0.8%
Specials
ValueCountFrequency (%)
39
97.5%
1
 
2.5%
None
ValueCountFrequency (%)
é 11
25.6%
° 9
20.9%
  8
18.6%
® 3
 
7.0%
à 2
 
4.7%
è 2
 
4.7%
â 2
 
4.7%
 1
 
2.3%
´ 1
 
2.3%
1
 
2.3%
Other values (3) 3
 
7.0%
Misc Symbols
ValueCountFrequency (%)
11
100.0%
Khmer
ValueCountFrequency (%)
5
20.8%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
2
 
8.3%
1
 
4.2%
1
 
4.2%
1
 
4.2%
Other values (4) 4
16.7%
Cyrillic
ValueCountFrequency (%)
а 4
18.2%
к 3
13.6%
у 2
9.1%
р 2
9.1%
г 2
9.1%
ш 2
9.1%
я 2
9.1%
Ч 1
 
4.5%
И 1
 
4.5%
б 1
 
4.5%
Other values (2) 2
9.1%
VS
ValueCountFrequency (%)
3
100.0%
Letterlike Symbols
ValueCountFrequency (%)
2
66.7%
1
33.3%
Dingbats
ValueCountFrequency (%)
1
100.0%
PUA
ValueCountFrequency (%)
1
100.0%

feedback_pr
Real number (ℝ)

ZEROS 

Distinct87
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.93581377
Minimum0
Maximum1.7252866
Zeros1073
Zeros (%)45.6%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:17.072976image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.7158172
Q31.7231533
95-th percentile1.7249331
Maximum1.7252866
Range1.7252866
Interquartile range (IQR)1.7231533

Descriptive statistics

Standard deviation0.85767375
Coefficient of variation (CV)0.91650046
Kurtosis-1.9709159
Mean0.93581377
Median Absolute Deviation (MAD)0.0092927821
Skewness-0.17509224
Sum2200.0982
Variance0.73560427
MonotonicityNot monotonic
2024-03-16T16:52:17.321148image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1073
45.6%
1.724578835 83
 
3.5%
1.722615178 69
 
2.9%
1.723867721 63
 
2.7%
1.725109985 59
 
2.5%
1.722435395 57
 
2.4%
1.724933142 57
 
2.4%
1.724223695 55
 
2.3%
1.724045813 53
 
2.3%
1.724756092 51
 
2.2%
Other values (77) 731
31.1%
ValueCountFrequency (%)
0 1073
45.6%
1.651555614 4
 
0.2%
1.666422113 1
 
< 0.1%
1.692745782 3
 
0.1%
1.695128536 1
 
< 0.1%
1.695557861 1
 
< 0.1%
1.696625999 1
 
< 0.1%
1.696838746 1
 
< 0.1%
1.697898118 4
 
0.2%
1.699369158 2
 
0.1%
ValueCountFrequency (%)
1.725286621 44
1.9%
1.725109985 59
2.5%
1.724933142 57
2.4%
1.724756092 51
2.2%
1.724578835 83
3.5%
1.724401369 44
1.9%
1.724223695 55
2.3%
1.724045813 53
2.3%
1.723867721 63
2.7%
1.723510907 28
 
1.2%

item_primary_price
Real number (ℝ)

HIGH CORRELATION 

Distinct1014
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4617537
Minimum0.0099011523
Maximum2.4255976
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:17.617469image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.0099011523
5-th percentile0.81405336
Q11.3016023
median1.4892265
Q31.6734641
95-th percentile1.925822
Maximum2.4255976
Range2.4156965
Interquartile range (IQR)0.37186183

Descriptive statistics

Standard deviation0.31759602
Coefficient of variation (CV)0.21727055
Kurtosis0.59520855
Mean1.4617537
Median Absolute Deviation (MAD)0.18423767
Skewness-0.60363383
Sum3436.5829
Variance0.10086723
MonotonicityNot monotonic
2024-03-16T16:52:17.881566image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.550394269 33
 
1.4%
1.397245709 31
 
1.3%
1.327595695 29
 
1.2%
1.07993242 29
 
1.2%
1.448822238 28
 
1.2%
1.2228885 27
 
1.1%
1.397363481 27
 
1.1%
1.489226459 26
 
1.1%
1.32776143 23
 
1.0%
1.448731891 23
 
1.0%
Other values (1004) 2075
88.3%
ValueCountFrequency (%)
0.009901152271 1
 
< 0.1%
0.5236241553 13
0.6%
0.5684157216 1
 
< 0.1%
0.5762340097 5
 
0.2%
0.588898039 2
 
0.1%
0.5938406449 2
 
0.1%
0.5987155221 1
 
< 0.1%
0.603524297 2
 
0.1%
0.6059043893 1
 
< 0.1%
0.6106169405 2
 
0.1%
ValueCountFrequency (%)
2.42559763 1
< 0.1%
2.313326068 1
< 0.1%
2.28491234 1
< 0.1%
2.253120985 1
< 0.1%
2.221790754 1
< 0.1%
2.216480708 1
< 0.1%
2.214916477 1
< 0.1%
2.200229481 1
< 0.1%
2.196101655 2
0.1%
2.177525817 1
< 0.1%

review_count
Real number (ℝ)

ZEROS 

Distinct69
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1293067
Minimum0
Maximum1105
Zeros2191
Zeros (%)93.2%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:18.116433image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum1105
Range1105
Interquartile range (IQR)0

Descriptive statistics

Standard deviation51.746751
Coefficient of variation (CV)10.088449
Kurtosis271.89759
Mean5.1293067
Median Absolute Deviation (MAD)0
Skewness15.680362
Sum12059
Variance2677.7263
MonotonicityNot monotonic
2024-03-16T16:52:18.351923image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2191
93.2%
1 19
 
0.8%
4 12
 
0.5%
3 9
 
0.4%
5 9
 
0.4%
2 6
 
0.3%
10 5
 
0.2%
22 5
 
0.2%
11 5
 
0.2%
9 3
 
0.1%
Other values (59) 87
 
3.7%
ValueCountFrequency (%)
0 2191
93.2%
1 19
 
0.8%
2 6
 
0.3%
3 9
 
0.4%
4 12
 
0.5%
5 9
 
0.4%
6 3
 
0.1%
7 3
 
0.1%
8 3
 
0.1%
9 3
 
0.1%
ValueCountFrequency (%)
1105 1
< 0.1%
986 1
< 0.1%
962 1
< 0.1%
844 1
< 0.1%
769 2
0.1%
608 1
< 0.1%
418 1
< 0.1%
392 2
0.1%
239 1
< 0.1%
211 1
< 0.1%

reasonable_shipping_cost
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2990642
Minimum0
Maximum5
Zeros295
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:18.594218image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.8
median4.9
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation1.6328852
Coefficient of variation (CV)0.3798234
Kurtosis3.0644268
Mean4.2990642
Median Absolute Deviation (MAD)0.1
Skewness-2.2406744
Sum10107.1
Variance2.666314
MonotonicityNot monotonic
2024-03-16T16:52:18.785906image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
5 1164
49.5%
4.9 403
 
17.1%
0 295
 
12.5%
4.8 294
 
12.5%
4.7 103
 
4.4%
4.6 52
 
2.2%
4.5 26
 
1.1%
4.4 10
 
0.4%
4.3 2
 
0.1%
4.2 1
 
< 0.1%
ValueCountFrequency (%)
0 295
12.5%
4.1 1
 
< 0.1%
4.2 1
 
< 0.1%
4.3 2
 
0.1%
4.4 10
 
0.4%
4.5 26
 
1.1%
4.6 52
 
2.2%
4.7 103
 
4.4%
4.8 294
12.5%
4.9 403
17.1%
ValueCountFrequency (%)
5 1164
49.5%
4.9 403
 
17.1%
4.8 294
 
12.5%
4.7 103
 
4.4%
4.6 52
 
2.2%
4.5 26
 
1.1%
4.4 10
 
0.4%
4.3 2
 
0.1%
4.2 1
 
< 0.1%
4.1 1
 
< 0.1%

item_no
Real number (ℝ)

Distinct1692
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6487083 × 1011
Minimum1.11701 × 1011
Maximum4.04555 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:19.014063image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum1.11701 × 1011
5-th percentile1.25651 × 1011
Q11.75968 × 1011
median2.74598 × 1011
Q33.53562 × 1011
95-th percentile4.038565 × 1011
Maximum4.04555 × 1011
Range2.92854 × 1011
Interquartile range (IQR)1.77594 × 1011

Descriptive statistics

Standard deviation9.2069051 × 1010
Coefficient of variation (CV)0.34759981
Kurtosis-1.2974827
Mean2.6487083 × 1011
Median Absolute Deviation (MAD)8.848 × 1010
Skewness-0.061351223
Sum6.2271132 × 1014
Variance8.4767102 × 1021
MonotonicityNot monotonic
2024-03-16T16:52:19.278535image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.25851 × 101118
 
0.8%
4.04551 × 101116
 
0.7%
1.15945 × 101116
 
0.7%
4.0455 × 101115
 
0.6%
1.85673 × 101115
 
0.6%
1.66382 × 101113
 
0.6%
3.9423 × 101112
 
0.5%
2.8552 × 101112
 
0.5%
3.35055 × 101111
 
0.5%
2.5626 × 101111
 
0.5%
Other values (1682) 2212
94.1%
ValueCountFrequency (%)
1.11701 × 10111
< 0.1%
1.12306 × 10111
< 0.1%
1.13884 × 10111
< 0.1%
1.13893 × 10111
< 0.1%
1.13904 × 10111
< 0.1%
1.13926 × 10111
< 0.1%
1.13934 × 10111
< 0.1%
1.13976 × 10111
< 0.1%
1.14123 × 10111
< 0.1%
1.14153 × 10111
< 0.1%
ValueCountFrequency (%)
4.04555 × 10115
 
0.2%
4.04554 × 10112
 
0.1%
4.04553 × 10113
 
0.1%
4.04551 × 101116
0.7%
4.0455 × 101115
0.6%
4.04548 × 10114
 
0.2%
4.04546 × 10113
 
0.1%
4.04545 × 10111
 
< 0.1%
4.04544 × 10111
 
< 0.1%
4.04542 × 10113
 
0.1%
Distinct1912
Distinct (%)81.3%
Missing0
Missing (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:19.795235image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length1332
Median length523
Mean length175.38367
Min length1

Characters and Unicode

Total characters412327
Distinct characters170
Distinct categories7 ?
Distinct scripts8 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1777 ?
Unique (%)75.6%

Sample

1st rowPerfect fit Arrived early than expected&Perfect fit Arrived early than expected&Perfect fit Arrived early than expected
2nd rowAwesome I found things I didnt even know my car had&Thank you&Mi Calificación es NEUTRAL porque el Vendedor hace una descripción correcta del producto pero para el Comprador no tiene sentido, NO RECOMIENDO HACER ESTA COMPRA porque vas a tener que comprar una licencia para poderlo usar que cuesta unos 100 y te incluye el lector, es decir por 100 hubiese tenido todo pero pague 137 por el lector atraves de esta compra y tuve que pagar 100 mas para la licencia, perdí mi dinero por no leer correctamente&Awesome I found things I didnt even know my car had&Smooth transaction&Smooth transaction
3rd rowGood seller, otem as described and packed well&Très bonne expérience&Arrived eventually
4th rowExactly as statedgreat vintage style Carolina tshirt&THANK YOU&Great buying experience Fast shipping, well packaged Would consider this seller again
5th rowRackety quack&Rackety quack&Missing critical connection piece for collar to work Seller sent me message that said Just Screw Ebay sent return label and refunded me&Good sale, Thank you
ValueCountFrequency (%)
and 2125
 
3.4%
the 1748
 
2.8%
seller 1271
 
2.0%
great 1244
 
2.0%
fast 1183
 
1.9%
as 1158
 
1.8%
i 1085
 
1.7%
thank 1059
 
1.7%
a 1040
 
1.6%
shipping 989
 
1.6%
Other values (6946) 50487
79.6%
2024-03-16T16:52:20.619730image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62799
15.2%
e 41920
 
10.2%
a 26240
 
6.4%
t 25143
 
6.1%
i 22297
 
5.4%
r 20853
 
5.1%
s 20068
 
4.9%
n 19105
 
4.6%
o 18841
 
4.6%
l 15452
 
3.7%
Other values (160) 139609
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 316949
76.9%
Space Separator 62799
 
15.2%
Uppercase Letter 21802
 
5.3%
Other Punctuation 9312
 
2.3%
Decimal Number 1145
 
0.3%
Control 256
 
0.1%
Other Letter 64
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 41920
13.2%
a 26240
 
8.3%
t 25143
 
7.9%
i 22297
 
7.0%
r 20853
 
6.6%
s 20068
 
6.3%
n 19105
 
6.0%
o 18841
 
5.9%
l 15452
 
4.9%
d 14783
 
4.7%
Other values (71) 92247
29.1%
Other Letter
ValueCountFrequency (%)
4
 
6.2%
4
 
6.2%
3
 
4.7%
3
 
4.7%
3
 
4.7%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
2
 
3.1%
Other values (30) 37
57.8%
Uppercase Letter
ValueCountFrequency (%)
T 2839
13.0%
A 2814
12.9%
I 2300
10.5%
G 1997
 
9.2%
E 1531
 
7.0%
S 1367
 
6.3%
F 928
 
4.3%
P 871
 
4.0%
N 744
 
3.4%
R 675
 
3.1%
Other values (24) 5736
26.3%
Decimal Number
ValueCountFrequency (%)
0 338
29.5%
1 200
17.5%
5 171
14.9%
2 116
 
10.1%
3 101
 
8.8%
4 74
 
6.5%
7 40
 
3.5%
6 39
 
3.4%
8 37
 
3.2%
9 29
 
2.5%
Other Punctuation
ValueCountFrequency (%)
& 6320
67.9%
, 2992
32.1%
Control
ValueCountFrequency (%)
252
98.4%
4
 
1.6%
Space Separator
ValueCountFrequency (%)
62799
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 338509
82.1%
Common 73512
 
17.8%
Cyrillic 232
 
0.1%
Hiragana 29
 
< 0.1%
Han 23
 
< 0.1%
Greek 10
 
< 0.1%
Katakana 7
 
< 0.1%
Hangul 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 41920
 
12.4%
a 26240
 
7.8%
t 25143
 
7.4%
i 22297
 
6.6%
r 20853
 
6.2%
s 20068
 
5.9%
n 19105
 
5.6%
o 18841
 
5.6%
l 15452
 
4.6%
d 14783
 
4.4%
Other values (66) 113807
33.6%
Cyrillic
ValueCountFrequency (%)
а 28
 
12.1%
о 26
 
11.2%
е 18
 
7.8%
с 15
 
6.5%
р 14
 
6.0%
в 12
 
5.2%
к 12
 
5.2%
и 11
 
4.7%
п 11
 
4.7%
н 10
 
4.3%
Other values (22) 75
32.3%
Hiragana
ValueCountFrequency (%)
4
13.8%
3
10.3%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
Other values (6) 6
20.7%
Common
ValueCountFrequency (%)
62799
85.4%
& 6320
 
8.6%
, 2992
 
4.1%
0 338
 
0.5%
252
 
0.3%
1 200
 
0.3%
5 171
 
0.2%
2 116
 
0.2%
3 101
 
0.1%
4 74
 
0.1%
Other values (5) 149
 
0.2%
Han
ValueCountFrequency (%)
4
17.4%
3
13.0%
3
13.0%
2
8.7%
2
8.7%
2
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (3) 3
13.0%
Greek
ValueCountFrequency (%)
ε 2
20.0%
ι 2
20.0%
α 2
20.0%
Κ 1
10.0%
ν 1
10.0%
κ 1
10.0%
σ 1
10.0%
Katakana
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 411750
99.9%
None 281
 
0.1%
Cyrillic 232
 
0.1%
Hiragana 29
 
< 0.1%
CJK 23
 
< 0.1%
Katakana 5
 
< 0.1%
Hangul 5
 
< 0.1%
Phonetic Ext 1
 
< 0.1%
Latin Ext Additional 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62799
15.3%
e 41920
 
10.2%
a 26240
 
6.4%
t 25143
 
6.1%
i 22297
 
5.4%
r 20853
 
5.1%
s 20068
 
4.9%
n 19105
 
4.6%
o 18841
 
4.6%
l 15452
 
3.8%
Other values (57) 139032
33.8%
None
ValueCountFrequency (%)
ä 51
18.1%
ö 34
12.1%
é 27
9.6%
á 25
8.9%
ü 22
7.8%
í 22
7.8%
ó 20
 
7.1%
è 18
 
6.4%
ú 10
 
3.6%
ã 9
 
3.2%
Other values (20) 43
15.3%
Cyrillic
ValueCountFrequency (%)
а 28
 
12.1%
о 26
 
11.2%
е 18
 
7.8%
с 15
 
6.5%
р 14
 
6.0%
в 12
 
5.2%
к 12
 
5.2%
и 11
 
4.7%
п 11
 
4.7%
н 10
 
4.3%
Other values (22) 75
32.3%
Hiragana
ValueCountFrequency (%)
4
13.8%
3
10.3%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
Other values (6) 6
20.7%
CJK
ValueCountFrequency (%)
4
17.4%
3
13.0%
3
13.0%
2
8.7%
2
8.7%
2
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (3) 3
13.0%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Phonetic Ext
ValueCountFrequency (%)
1
100.0%
Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Latin Ext Additional
ValueCountFrequency (%)
1
100.0%

no_of_comments
Real number (ℝ)

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6882178
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size101.3 KiB
2024-03-16T16:52:20.856000image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q35
95-th percentile6
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4232811
Coefficient of variation (CV)0.38589943
Kurtosis-0.3421834
Mean3.6882178
Median Absolute Deviation (MAD)0
Skewness0.64241077
Sum8671
Variance2.0257292
MonotonicityNot monotonic
2024-03-16T16:52:21.050358image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3 1459
62.1%
6 498
 
21.2%
4 153
 
6.5%
1 128
 
5.4%
5 72
 
3.1%
7 21
 
0.9%
2 17
 
0.7%
8 2
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
1 128
 
5.4%
2 17
 
0.7%
3 1459
62.1%
4 153
 
6.5%
5 72
 
3.1%
6 498
 
21.2%
7 21
 
0.9%
8 2
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 2
 
0.1%
7 21
 
0.9%
6 498
 
21.2%
5 72
 
3.1%
4 153
 
6.5%
3 1459
62.1%
2 17
 
0.7%
1 128
 
5.4%

Interactions

2024-03-16T16:52:09.731825image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:52.490408image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:54.393893image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:56.599255image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:58.400871image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:00.262692image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:02.179633image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:04.004504image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:05.917511image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:07.794054image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:09.941400image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:52.717095image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:54.617571image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:56.780878image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:58.622860image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:00.440423image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:02.349901image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:04.189161image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:06.098378image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:07.966951image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:10.185167image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:52.896970image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:54.792428image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:56.954482image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:58.794182image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:00.659617image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:02.551929image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:04.364646image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:06.298761image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:08.142268image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:10.377199image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:53.061803image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:54.967720image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:57.123351image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:58.985742image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:00.839493image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:02.729950image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:04.557123image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:06.471845image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:08.314079image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:10.608123image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:53.232755image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:55.149240image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:57.293936image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:59.151482image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:01.030470image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:02.899413image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:04.747962image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:06.669563image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:08.510797image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:10.796752image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:53.416404image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:55.711964image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:57.479068image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:59.330812image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:01.216980image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:03.086267image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:04.938193image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:06.857466image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:08.739228image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:10.985773image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:53.636559image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:55.875856image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:57.698449image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:59.506574image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:01.392931image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:03.256390image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:05.149364image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:07.044884image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:08.908853image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:11.168466image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:53.823183image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:56.044507image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:57.872401image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:59.702295image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:01.620497image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:03.431114image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:05.316994image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:07.220525image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:09.106094image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:11.343900image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:53.996237image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:56.208176image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:58.035798image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:59.884576image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:01.805544image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:03.642901image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:05.528744image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:07.390684image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:09.277839image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:11.563464image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:54.172267image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:56.381897image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:51:58.215028image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:00.071222image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:01.983879image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:03.817968image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:05.731529image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:07.601503image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2024-03-16T16:52:09.462647image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Correlations

2024-03-16T16:52:21.215356image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
item_approx_priceaccurate_descriptioncommunicationshipping_speedfeedback_pritem_primary_pricereview_countreasonable_shipping_costitem_nono_of_comments
item_approx_price1.0000.0660.0540.222-0.0410.7850.183-0.071-0.0780.002
accurate_description0.0661.0000.6940.6850.101-0.081-0.0170.254-0.0760.160
communication0.0540.6941.0000.7220.181-0.1100.0000.346-0.0920.172
shipping_speed0.2220.6850.7221.0000.1660.0400.0470.241-0.1150.192
feedback_pr-0.0410.1010.1810.1661.000-0.1690.0870.400-0.0480.356
item_primary_price0.785-0.081-0.1100.040-0.1691.0000.190-0.254-0.003-0.183
review_count0.183-0.0170.0000.0470.0870.1901.0000.046-0.0550.076
reasonable_shipping_cost-0.0710.2540.3460.2410.400-0.2540.0461.000-0.0120.450
item_no-0.078-0.076-0.092-0.115-0.048-0.003-0.055-0.0121.000-0.101
no_of_comments0.0020.1600.1720.1920.356-0.1830.0760.450-0.1011.000

Missing values

2024-03-16T16:52:12.255726image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T16:52:12.672017image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

item_approx_priceaccurate_descriptionseller_namecommunicationshipping_speedtitlefeedback_pritem_primary_pricereview_countreasonable_shipping_costitem_nocommentno_of_comments
00.0000004.9pearlwholesale4.94.9Fashion Silver Zircon Christmas Xmas Elk Earrings Stud Women Party Jewelry Gift1.7226150.75526305.02.350810e+11Perfect fit Arrived early than expected&Perfect fit Arrived early than expected&Perfect fit Arrived early than expected3
31.8334974.9dragonemad5.05.0Carly Universal Scanner BMW Diagnostic Best App (iOS/Android) OBD Reader+GIFT !!0.0000001.783004264.91.238800e+11Awesome I found things I didnt even know my car had&Thank you&Mi Calificación es NEUTRAL porque el Vendedor hace una descripción correcta del producto pero para el Comprador no tiene sentido, NO RECOMIENDO HACER ESTA COMPRA porque vas a tener que comprar una licencia para poderlo usar que cuesta unos 100 y te incluye el lector, es decir por 100 hubiese tenido todo pero pague 137 por el lector atraves de esta compra y tuve que pagar 100 mas para la licencia, perdí mi dinero por no leer correctamente&Awesome I found things I didnt even know my car had&Smooth transaction&Smooth transaction6
61.3421634.7Seven Star Solutions4.84.8Aqua Red Perfume For Men, Long Lasting & Smooth Jasmine Fragrance 60 ml0.0000001.26368805.03.746160e+11Good seller, otem as described and packed well&Très bonne expérience&Arrived eventually3
71.4025924.9adalyn19735.05.0Alfred's Basic Piano Library lot of 3 Lesson, Act/Ear Train, Solo Level A0.0000001.32776104.93.855110e+11Exactly as statedgreat vintage style Carolina tshirt&THANK YOU&Great buying experience Fast shipping, well packaged Would consider this seller again3
80.9659484.2ray_60490.05.0PetSpy N10 Ultrasonic Dog Bark Deterrent, 2 Frequency Modes, Barking Control Dog1.6955580.86974204.51.259120e+11Rackety quack&Rackety quack&Missing critical connection piece for collar to work Seller sent me message that said Just Screw Ebay sent return label and refunded me&Good sale, Thank you4
141.0194094.8rockgemstonehome4.94.9Raw Natural Labradorite Leaf Shape Pendant Quartz Crystal Stone Necklace Healing0.0000000.92493305.03.547000e+11Pretty &Great&Beautiful necklace Love it Exactly as pictured&Cute thank you Got here super fast&Beautiful great pictures&The product was better than advertised Delivery was right on time I live in Reno there are plenty of rock and gem shops here This crystal is better for my money than I can get here, thanks6
161.4024774.6kaymomshopper4.65.0Thomas and Friends Radio Karaoke Portable FM Radio with Microphone S71.7158171.32759604.62.654770e+11Item as described, A&Arrived on time brand new as described Excellent transaction&Item as description Quick shipping and delivery Updates and tracking Arrived in a timely manner3
201.6713024.9health-solution-prime5.04.9Vitamins And Dietary Supplements - ELK VELVET ANTLER - Overall wellness - 1 B1.7224351.61184505.03.350550e+11Excellent&Never received the product nor communication fro seller&Fast shipping3
211.8803074.9smallenginesforless4.85.0GCV 200 Honda 6hp Motor 7/8" x 1-7/8" Vertical Shaft Engine1.7211711.83210504.92.559230e+11Quick shipping havent installed on splitter yet but sure it will be ok&no good i never recibe the motor gcv 200 honda&I sent it back unopened and I never got credited back on my credit card&fast shipment, as described, Thanks&Would have been on time if not for the postal service sending it to the wrong place&Great NOS machine, blocked and ziptied on pallet, courteous delivery Had one issue with machine, but this was promptly resolved by seller Hope this machine lasts a while, but would order from this seller again6
221.2643574.9zhengzheng20114.94.9Pet Mail Carrier Costume Soft Funny Costumes Pet Suit With Cap For Small Dog ZZ11.7215331.30207105.02.350680e+11Works great&Seller kept communication open until I received my item &Great seller, would definitely recommend3
item_approx_priceaccurate_descriptionseller_namecommunicationshipping_speedtitlefeedback_pritem_primary_pricereview_countreasonable_shipping_costitem_nocommentno_of_comments
57891.7945910.0nicholasc7030.00.0Nike SB Dunk Low Mystic Red Rosewood (DV5429-601) US Men’s Size 100.0000001.74213700.01.453730e+11Item delivered as advertised Good transaction&Great seller AAA&Por favor pone esta dirección \n1210 Loring ave apt 5H \nBrooklyn 112083
57900.0000004.8CheapPCio4.74.8New ListingLenovo ThinkCentre M700 Tiny Desktop i5 6500T 8GB 256GB SSD WIN 10 PRO1.7148751.80523605.03.551140e+11A computer arrived safe and sound everything working great and strong hardware for the price&Fast Shipping&Good item, works flawlessly Perfect transaction, thanks3
57921.1164934.9Baseus Official Online Store5.05.0Baseus 100W USB C to Type C Charger Cable Fast Charge Lead Laptop Data Cord 1m1.7244011.02607405.03.132390e+11Fine Business&Perfect&Fast Shipping, Recommend Seller, Great Communication, Great Prices, Items Exactly as Described, Will buy from again thanks&Excellent&Great product Super fast shipping A&Great item Fast shipping6
57951.8873524.9typique1234.95.0Sony PlayStation 2 PS2 Fat Console System Bundle 1 Controller1.7217141.8394868445.03.861040e+11Works great,\n thanx&Great condition Fast shipping&I got a fat PS2 and it works great It was shipped fast and secure, thank you&Works great,\n thanx&Great condition Fast shipping&Thank You6
57961.7039240.0disneygirl1290.00.0Hello Kitty Christmas Blanket Throw 2023 Plush NWT Santa Sanrio 50x70 Viral…0.0000001.64666700.01.960310e+11Nice new dress Great price Fast delivery&Very Nice &A seller Would buy from again3
57971.9564644.6PennySiouxPC4.64.7Custom White Gaming Desktop PC Intel i7 Quad 8 GB 1 TB Nvidia Quadro K620 2 GB1.7231531.91179105.02.039710e+11Great pc&It went great product was well what it said it was excellent choice very happy&&Great pc&all good&Great product, arrived in good shape thanks6
57981.4561754.9sun-share5.05.0ELUTO 12V Electric Blanket Heated Throw Heating Blanket Winter Car Home Winter1.7224351.38460005.03.743820e+11Works as it should&As described & fast shipping Great&Received my purchase within days and Thank you, very pleased with the blanket&Thanks&Works as it should&Exactly as advertised Quality product Arrived before scheduled date Thank you7
58011.4682894.9radium_ari4.94.916mm leather handmade WW1 WW2 military trench wrist watch bund band cuff strap1.7247561.39736305.02.562070e+11Great service AAAAA&awsome thank you&Ok3
58021.5406574.9watchhubstore4.94.9Seiko Slim Quartz Men's Gold Plated Japanese Wrist Watch With New Battery1.7249331.47406505.01.345290e+11A very nice working watch My compliments to the seller&Fast shipping Good quality Im really pleased with the watch\nRecommend&Oggetto come descritto Importazione ITA da pagare al ricevimento Ottimo Ebayer3
58041.3861015.0darkkside_995.05.0Star Wars Black Series Tusken Raider Mandalorian 6" Figure Credit Collection Toy0.0000001.31032605.01.261370e+11Item arrived on time and in excellent condition&Arrived as described Thank you&Item was as described and arrived in good condition3

Duplicate rows

Most frequently occurring

item_approx_priceaccurate_descriptionseller_namecommunicationshipping_speedtitlefeedback_pritem_primary_pricereview_countreasonable_shipping_costitem_nocommentno_of_comments# duplicates
01.5080904.9cynmccl_24.95.0Revlon One Step Volumizer plus 2.0 Hair Dryer and Hot Air Brush | Dry and Style1.7222551.43956904.73.350660e+11Received as described Love it Thank you&Perfect transaction&Great Product32
11.5331130.0Antiquoe0.00.0ANCIENT ROMAN WARRIOR RING SILVER AUTHENTIC HISTORIC ARTIFACT AMAZING ENGRAVINGS0.0000001.46607700.01.663650e+11Coin is exactly as described Shipping was great Will buy from this seller again&Good22
21.6863510.0hlou_460.00.0ANCIENT ROMAN WARRIOR RING SILVERRD ENGRAVED AUTHENTIC HISTORIC ARTIFACT0.0000001.62813100.01.960310e+11012
31.7093704.7collectors_hot_spot4.95.0Super Nintendo Classic Edition Mini- 21 Games1.7180551.65240304.73.258480e+11Great seller Thank you&Smooth transaction, the SNES Classic came in absolutely fantastic condition, could not be happier with it as a used item \n\nExcellent experience, fast shipment, highly recommend A eBayer&Thank you for the great price, and speedy shipping32
42.1232270.0i Crafts Gallery0.00.0New ListingOnyx Cube Table, Plinth Living Room Table with Marble Stand1.6927462.08547200.03.645340e+11Seems good without any bubles good work by craftman good comunication and fast shipping&Very beautiful Craftsmanship, resin was upto mark, there was no bubble and air in the raisin as committed, fastest delivery, 24 hour service is just a cherry on cake 5 Star Rating 100 recommended\nI love the table and will surely order another one for my new house \nThank you I Crafts gallery&Very beautiful product exactly what i was looking for superb communication with tha seller during production and very fast and secure delivery Highly recommended seller32